Multiobjective Evolutionary Algorithms and Applications

Capa
Springer Science & Business Media, 04/05/2005 - 295 páginas
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Multiobjective Evolutionary Algorithms and Applications provides comprehensive treatment on the design of multiobjective evolutionary algorithms and their applications in domains covering areas such as control and scheduling. Emphasizing both the theoretical developments and the practical implementation of multiobjective evolutionary algorithms, a profound mathematical knowledge is not required.

Written for a wide readership, engineers, researchers, senior undergraduates and graduate students interested in the field of evolutionary algorithms and multiobjective optimization with some basic knowledge of evolutionary computation will find this book a useful addition to their book case.

 

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Índice

Introduction
1
12 Multiobjective Optimization
5
13 Preview of Chapters
6
Review of MOEAs
9
22 Survey of MOEAs
10
23 Development Trends
14
24 Outline of Algorithms
15
25 Conclusions
29
834 Test Problem of TLK2
133
84 Simulation Studies
134
85 Conclusions
148
A Multiobjective Evolutionary Algorithm Toolbox
151
92 Roles and Features of MOEA Toolbox
152
922 Advanced Settings
159
923 Model File
162
93 Conclusions
164

Conceptual Framework and Distribution Preservation Mechanisms for MOEAs
31
321 Individual Assessment
32
322 Elitism
34
323 Density Assessment
36
33 Distribution Preservation Mechanisms
38
332 Evaluation and Comparison
42
34 Conclusions
49
Decision Supports and Advanced Features for MOEAs
51
421 Paretobased Domination with Goal Information
52
422 GoalSequence Domination Scheme with SoftHard Priority Specifications
53
423 Optimization with SoftHard Constraints
57
424 Logical Connectives Among Goal and Priority Specifications
58
43 A Multiobjective Evolutionary Algorithm
59
432 MOEA Program Flowchart
61
433 Convergence Trace for MO Optimization
63
44 Simulation Studies
64
45 Conclusions
73
Dynamic Population Size and Local Exploration for MOEAs
75
52 Incrementing Multiobjective Evolutionary Algorithm
76
522 Fuzzy Boundary Local Perturbation
77
523 Program Flowchart of IMOEA
81
53 Simulation Studies
83
54 Conclusions
89
A Distributed Cooperative Coevolutionary Multiobjective Algorithm
91
62 A Cooperative Coevolutionary Algorithm
92
622 Adaptation of Cooperative Coevolution for MO Optimization
93
623 Extending Operator
95
624 Flowchart of CCEA
96
63 A Distributed Cooperative Coevolutionary Algorithm
97
632 A Distributed CCEA DCCEA
98
633 Implementation of DCCEA
99
634 Workload Balancing
102
642 MO Test Problems
103
644 Simulation Results of DCCEA
107
65 Conclusions
110
Learning the Search Range in Dynamic Environments
111
72 Adaptive Search Space
112
73 Simulation Studies
114
732 MO Optimization I
119
733 MO Optimization II
120
74 Conclusions
122
Performance Assessment and Comparison of MOEAs
125
83 MO Test Problems
127
831 Test Problems of ZDT1 ZDT2 ZDT3 ZDT4 and ZDT6
129
832 Test Problems of FON KUR and POL
131
833 Test Problem of TLK
132
Evolutionary ComputerAided Control System Design
165
102 Performancebased Design Unification and Automation
166
1022 Control System Formulation
167
1023 Performance Specifications
168
103 Evolutionary ULTIC Design Application
173
104 Conclusions
182
Evolutionary Design Automation of Multivariable QFT Control System
183
112 Problem Formulation
185
1122 MO QFT Design Formulation
187
113 MIMO QFT Control Problem
193
114 Conclusions
202
Evolutionary Design of HDD Servo Control System
203
122 The Physical HDD Model
204
123 Design of HDD Servo Control System
206
1232 Evolutionary Design
208
1233 Conventional Controllers
211
1234 Robustness Validation
213
1235 RealTime Implementation
216
124 Conclusions
217
Evolutionary Scheduling VRPTW
219
132 The Problem Formulation
221
1322 Solomons 56 Benchmark Problems for VRPTW
224
133 A Hybrid Multiobjective Evolutionary Algorithm
226
1331 Multiobjective Evolutionary Algorithms in Combinatorial Applications
227
1333 VariableLength Chromosome Representation
229
1334 Specialized Genetic Operators
230
1335 Pareto Fitness Ranking
232
1336 Local Search Exploitation
234
134 Simulation Results and Comparisons
235
1343 Specialized Operators and Hybrid Local Search Performance
239
1344 Performance Comparisons
241
135 Conclusions
247
Evolutionary SchedulingTTVRP
249
142 The Problem Scenario
250
1421 Modeling the Problem Scenarios
251
1422 Mathematical Model
253
1423 Generation of Test Cases
256
143 Computation Results
258
1431 MO Optimization Performance
259
1432 Computation Results for TEPC and LTTC
265
1433 Comparison Results
268
144 Conclusions
271
Bibliography
273
Index
293
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Passagens conhecidas

Página 290 - Zames G (1966) On the input-output stability of time- varying nonlinear feedback systems- Parts I and II.
Página 279 - State-space formulae for all stabilizing controllers that satisfy an -//.^ norm bound and relations to risk sensitivity.
Página 282 - Roucairol (Eds.), Meta-heuristics, Advances and Trends in Local Search Paradigms for Optimization, Kluwer Academic Publishers, 1999, pp.

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